Implementing Open and Standardized Data Practices in Musculoskeletal Imaging: ORMIR and UMUD

Abstract

Due to the increasing amount of research data, open and reproducible data practices will define the future of medical research. Despite strong conceptual frameworks such as FAIR (Findable, Accessible, Interoperable, Reusable), implementation across laboratories remains inconsistent and fragmented. The MoveD (Haas et al., 2024) initiative outlines open, FAIR, and reproducible data practices in human movement research. However, putting such frameworks into operation remains challenging, especially in imaging-based disciplines, where data are heterogeneous and often under proprietary ecosystems. The Open and Reproducible Musculoskeletal Imaging Research (ORMIR) community and the Universal Musculoskeletal Ultrasonography Database (UMUD) address this issue by implementing reproducible data sharing in musculoskeletal imaging (Bonaretti et al., 2025; Ritsche et al., 2025). Here, we demonstrate implementation of guideline-based, reproducible data practices showcasing the ORMIR Medical Imaging Data Structure (MIDS) and UMUD.

One of ORMIR’s aims is to create technical standards for organizing and sharing musculoskeletal imaging data across modalities and disciplines such as MRI, CT, and ultrasound. ORMIR-MIDS defines a transparent folder hierarchy, file-naming conventions, and a metadata scheme that ensure imaging datasets are both human-readable and machine-interpretable. A publicly available Python implementation enables validation, anonymization, and bidirectional conversion between ORMIR-MIDS and common vendor formats, lowering the technical barriers to adoption. Importantly, ORMIR-MIDS is not only a data structure but also a mechanism for community convergence—encouraging laboratories to align their workflows with shared standards that support cross-study comparability, reproducibility, and long-term reusability.

UMUD offers an example of how such standards can be applied in ultrasonography research. It provides an openly available webapp that indexes metadata from publicly available musculoskeletal ultrasound datasets hosted on open platforms such as Zenodo. Using a standardized metadata scheme derived from ORMIR and MoveD principles, UMUD enhances the discoverability and comparability of datasets, linking them through descriptors based on expert consensus. By providing contribution and data structuring instructions, UMUD allows the research community to easily contribute their data. UMUD demonstrates how open research data can actively support both methodological innovation and capacity building in the research community.

Together, ORMIR and UMUD embody the transition from conceptual to actionable open science. They illustrate how principles articulated in MoveD and FAIR can be realized through interoperable standards, shared infrastructure, and collaboration between technical and applied domains.

References

Bonaretti, S., Barzegari, M., Bevers, M., Boyd, S., Burghardt, A. J., Cameron, D., Chiumento, F., Crimi, G., Degenhart, G., Durongbhan, P., Hernandez, M. A. E., Fraterrigo, G., Ghasem-Zadeh, A., Grassi, L., Hirvasniemi, J., Hosseinitabatabaei, M., Iori, G., Kok, J., Kuczynski, M., … Zukic, D. (2025). Open and reproducible research in musculoskeletal imaging: Why it matters and how to implement it with the guidelines of the ORMIR community. https://doi.org/10.5281/zenodo.17258830

Haas, M. C., Sommer, B. B., Van Rekum, S., Moerman, F., & Graf, E. S. (2024, November). MoveD - open research data guidelines for movement laboratories. Zenodo. https://doi.org/10.5281/zenodo.14179954

Ritsche, P., Sarto, F., Santini, F., Leitner, C., Franchi, M., Faude, O., Finni, T., Seynnes, O., & Cronin, N. (2025). UMUD: A Web Application for Easy Access to Musculoskeletal Ultrasonography Datasets. Open Science Framework. https://doi.org/10.31219/osf.io/syr4z